Given the high diversity in perturbations in this study, the data are a good candidate to perform Weighted Gene Correlation Network Analysis. We will focus on specific downstream targets of kinases, which will give us course grained groupings of sites. This should help us recognize pathway crosstalk even for well established kinase targets.
Meta data for this report are available in:
yeast_phospho_data_processed/site_data_v2/meta_runs_samples.csvCorrected and imputed data can be found in:
yeast_phospho_data_processed/site_data_v2/batch_correction/data_psites.vfilt.50.qrilc.rep1.corrected.csv##
## Call:
## lm(formula = coef ~ group + treatment, data = .)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.9811 -0.7115 -0.5304 0.7192 1.5355
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.78699 0.39829 4.487 0.000167 ***
## groupgroup_2 1.63640 0.34851 4.695 9.94e-05 ***
## treatmentKC 0.04444 0.48781 0.091 0.928204
## treatmentNC 0.05656 0.48781 0.116 0.908705
## treatmentSO 0.22038 0.48781 0.452 0.655659
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9126 on 23 degrees of freedom
## Multiple R-squared: 0.4921, Adjusted R-squared: 0.4037
## F-statistic: 5.571 on 4 and 23 DF, p-value: 0.002755
## # A tibble: 4 × 6
## site treatment coef p.value adj.p.value regulated
## <chr> <chr> <dbl> <dbl> <dbl> <lgl>
## 1 YLR113W_Y_176 CA 0.961 0.347 0.766 FALSE
## 2 YLR113W_Y_176 KC 4.23 0.00000127 0.0000972 TRUE
## 3 YLR113W_Y_176 NC 1.44 0.0955 0.460 FALSE
## 4 YLR113W_Y_176 SO 3.65 0.0000272 0.00130 TRUE
## Warning: executing %dopar% sequentially: no parallel backend registered
## Power SFT.R.sq slope truncated.R.sq mean.k. median.k. max.k.
## 1 1 0.7850 1.820 0.871 159.000 164.000 220.00
## 2 2 0.0715 0.229 0.565 59.500 59.800 108.00
## 3 3 0.1920 -0.388 0.705 27.000 25.000 62.20
## 4 4 0.4250 -0.816 0.790 13.900 11.500 39.80
## 5 5 0.6050 -1.120 0.882 7.810 5.930 27.30
## 6 6 0.7060 -1.300 0.911 4.690 3.130 19.70
## 7 7 0.7750 -1.440 0.936 2.980 1.820 14.60
## 8 8 0.8220 -1.460 0.959 1.970 1.080 11.10
## 9 9 0.8350 -1.510 0.968 1.350 0.695 8.63
## 10 10 0.8550 -1.500 0.970 0.958 0.448 6.78
## Warning: Removed 1 rows containing missing values (geom_point).
## ..cutHeight not given, setting it to 0.998 ===> 99% of the (truncated) height range in dendro.
## ..done.
## dynamicColors
## blue brown grey turquoise
## 174 164 70 230
## Power SFT.R.sq slope truncated.R.sq mean.k. median.k. max.k.
## 1 1 0.5360 1.870 0.797 227.00 233.000 322.00
## 2 2 0.0715 0.274 0.631 82.30 82.500 151.00
## 3 3 0.1830 -0.466 0.689 36.60 34.400 86.20
## 4 4 0.4400 -0.923 0.822 18.50 15.800 54.90
## 5 5 0.6410 -1.210 0.913 10.20 7.810 37.60
## 6 6 0.7590 -1.340 0.942 6.07 4.130 26.90
## 7 7 0.8100 -1.440 0.948 3.81 2.260 19.90
## 8 8 0.8590 -1.480 0.969 2.50 1.340 15.00
## 9 9 0.8810 -1.470 0.979 1.71 0.830 11.70
## 10 10 0.8530 -1.540 0.943 1.21 0.525 9.36
## ..cutHeight not given, setting it to 0.998 ===> 99% of the (truncated) height range in dendro.
## ..done.
## dynamicColors
## black blue brown green grey magenta pink red
## 44 171 140 58 63 23 27 52
## turquoise yellow
## 287 69
## Scale for 'y' is already present. Adding another scale for 'y', which will
## replace the existing scale.
## Warning: Removed 23 rows containing missing values (geom_text).
## Removed 23 rows containing missing values (geom_text).
## Power SFT.R.sq slope truncated.R.sq mean.k. median.k. max.k.
## 1 1 0.1630 0.6390 0.386 55.000 56.700 80.40
## 2 2 0.0275 0.0972 0.568 23.300 23.900 41.80
## 3 3 0.1650 -0.2080 0.716 11.500 11.000 24.70
## 4 4 0.3690 -0.5640 0.646 6.370 5.750 15.80
## 5 5 0.5600 -0.7070 0.762 3.800 3.080 10.80
## 6 6 0.7490 -0.8080 0.837 2.420 1.800 7.66
## 7 7 0.8070 -0.8870 0.834 1.630 1.100 5.68
## 8 8 0.9040 -0.9210 0.967 1.150 0.740 4.37
## 9 9 0.9400 -0.9360 0.956 0.849 0.543 3.46
## 10 10 0.8290 -1.0200 0.797 0.651 0.410 2.82
## ..cutHeight not given, setting it to 0.996 ===> 99% of the (truncated) height range in dendro.
## ..done.
## dynamicColors
## blue grey turquoise
## 66 42 73